Databricks предлагает четко очерченную руководящую роль в быстрорастущей компании в сфере данных и ИИ, с зарплатой выше рыночного ориентира и заметным влиянием на инфраструктурную стратегию.
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Hirify AI/Оригинал
TL;DR
Senior Manager, Infrastructure Data Science (Data Science/ML): Shaping the future of Databricks infrastructure through data science, tackling complex challenges related to capacity planning, performance optimization, and reliability engineering. Focus on implementing data-driven solutions to mitigate infrastructure risks, improve resource utilization, and mentor a team of data scientists.
Location: San Francisco, California, United States
Salary: $228,600–$314,250 USD annually for Zone 1; additional bonus, equity, and benefits may apply.
Company
Databricks builds and operates a data and AI infrastructure platform used by organizations worldwide for data applications, analytics, and AI workloads.
What you will do
Provide strategic guidance on infrastructure planning, capacity, scalability, and cost-effectiveness.
Use data science and analytics to guide infrastructure decisions and influence engineering and support stakeholders.
Develop solutions to predict and mitigate infrastructure risks and failures, improving reliability, performance, and uptime.
Analyze infrastructure usage to improve resource utilization, reduce inefficiencies, and optimize costs.
Build data frameworks that help support teams troubleshoot and resolve product issues more quickly.
Hire, manage, and mentor a team of data scientists while establishing best practices for scalable infrastructure solutions.
Requirements
10+ years of experience in infrastructure data science, machine learning, or advanced analytics in high-growth companies.
5+ years of experience managing, hiring, and developing teams.
Experience developing data science, analytics, machine learning, and AI products or capabilities in a cloud environment.
Knowledge of statistics, rigorous analytical techniques, data visualization, data engineering, data modeling, and big data technologies.
Leadership and communication skills, including the ability to influence executives and senior management across organizational lines.
MS or PhD in statistics, mathematics, computer science, engineering, or another quantitative field.
Culture & Benefits
Work on highly technical data and AI infrastructure products operating at significant scale.
Collaborative environment focused on innovation, resilience, security, and customer success.
Comprehensive benefits and perks, varying by region.
Inclusive hiring practices and a commitment to diversity and equal employment opportunity.
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